Introduction

To illustrate the usage of CytoTree on differential trajectory reconstruction of time-course FCS data, we used a flow cytometry dataset of ten-day hematopoietic differentiation from the hESC line HUES9. By adding different cytokine combinations on different days, HUES9 cells (CD90+CD49f+ on Day 0, D0) were directionally differentiated into mesodermal cells (FLK1+, D4), hemogenic endothelium (CD34+CD31+CD43-, D6) and hematopoietic stem/progenitor cells (HSPCs, CD34+CD43+CD38-CD45RA-CD90+, D8) in succession. Ten cell surface markers (CD90, CD49f, FLK1, CD34, CD31, CD73, CD43, CD45, CD45RA, and CD38) were used for the flow cytometry analysis to monitor the generation of these cells.

Preprocessing

## 2020-06-20 01:09:03 Number of cells in processing: 15000
## 2020-06-20 01:09:03 rownames of meta.data and raw.data will be named using column cell
## 2020-06-20 01:09:03 Index of markers in processing
## 2020-06-20 01:09:03 Creating CYT object.
## 2020-06-20 01:09:03 Determining normalization factors
## 2020-06-20 01:09:03 Normalization and log-transformation.
## 2020-06-20 01:09:03 Build CYT object succeed

Trajectory

## 2020-06-20 01:09:10 Calculating FlowSOM.
## 2020-06-20 01:09:10 Calculating FlowSOM completed.
## 2020-06-20 01:09:10 Calculating PCA.
## 2020-06-20 01:09:11 Calculating PCA completed.
## 2020-06-20 01:09:11 Calculating tSNE.
## 2020-06-20 01:10:30 Calculating tSNE completed.
## 2020-06-20 01:10:30 Calculating Diffusion Map.
## 2020-06-20 01:10:30 Destiny determined an optimal global sigma: 0.865
## 2020-06-20 01:11:13 Calculating Diffusion Map completed
## 2020-06-20 01:11:13 Calculating Umap.
## 2020-06-20 01:13:21 Calculating Umap.
## 2020-06-20 01:13:21 Calculating buildTree.
## 2020-06-20 01:13:21 Initialization for root.cells and leaf cells
## 2020-06-20 01:13:21 Calculating buildTree completed.

Pseudotime

## 2020-06-20 01:13:29 954 cells will be added to root.cells .
## 2020-06-20 01:13:29 Calculating Pseudotime.
## 2020-06-20 01:13:29 Pseudotime exists in meta.data, it will be replaced.
## 2020-06-20 01:13:29 The log data will be used to calculate pseudotime
## 2020-06-20 01:14:06 Calculating Pseudotime completed.

Intermediate state analysis

## 2020-06-20 01:14:35 Calculating FlowSOM.
## 2020-06-20 01:14:35 Calculating FlowSOM completed.
## 2020-06-20 01:14:35 Calculating PCA.
## 2020-06-20 01:14:35 Calculating PCA completed.
## 2020-06-20 01:14:35 Calculating Diffusion Map.
## 2020-06-20 01:14:36 Destiny determined an optimal global sigma: 0.816
## 2020-06-20 01:14:39 Calculating Diffusion Map completed
## 2020-06-20 01:14:39 Calculating buildTree.
## 2020-06-20 01:14:39 The log data will be used to calculate trajectory
## 2020-06-20 01:14:39 Initialization for root.cells and leaf cells
## 2020-06-20 01:14:39 Calculating buildTree completed.
## 2020-06-20 01:14:39 654 cells will be added to root.cells .
## 2020-06-20 01:14:39 Calculating Pseudotime.
## 2020-06-20 01:14:39 Pseudotime exists in meta.data, it will be replaced.
## 2020-06-20 01:14:39 The log data will be used to calculate pseudotime
## 2020-06-20 01:14:41 Calculating Pseudotime completed.

Bug Reports

If there is any error in installing or librarying the CytoTree package, please contact us via e-mail

Session information

## R version 4.0.0 (2020-04-24)
## Platform: x86_64-apple-darwin17.0 (64-bit)
## Running under: macOS Catalina 10.15.5
## 
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRblas.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/4.0/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## 
## other attached packages:
## [1] pheatmap_1.0.12 stringr_1.4.0   CytoTree_0.99.6 igraph_1.2.5   
## [5] flowViz_1.52.0  lattice_0.20-41 flowCore_2.0.1  LSD_4.0-0      
## [9] ggplot2_3.3.1  
## 
## loaded via a namespace (and not attached):
##   [1] reticulate_1.16             RUnit_0.4.32               
##   [3] tidyselect_1.1.0            RSQLite_2.2.0              
##   [5] AnnotationDbi_1.50.0        grid_4.0.0                 
##   [7] ranger_0.12.1               BiocParallel_1.22.0        
##   [9] Rtsne_0.15                  scatterpie_0.1.4           
##  [11] munsell_0.5.0               destiny_3.2.0              
##  [13] codetools_0.2-16            umap_0.2.5.0               
##  [15] withr_2.2.0                 colorspace_1.4-1           
##  [17] Biobase_2.48.0              knitr_1.28                 
##  [19] stats4_4.0.0                SingleCellExperiment_1.10.1
##  [21] robustbase_0.93-6           vcd_1.4-7                  
##  [23] VIM_6.0.0                   TTR_0.23-6                 
##  [25] labeling_0.3                GenomeInfoDbData_1.2.3     
##  [27] polyclip_1.10-0             bit64_0.9-7                
##  [29] farver_2.0.3                flowWorkspace_4.0.6        
##  [31] vctrs_0.3.1                 generics_0.0.2             
##  [33] xfun_0.14                   ggthemes_4.2.0             
##  [35] R6_2.4.1                    GenomeInfoDb_1.24.0        
##  [37] RcppEigen_0.3.3.7.0         rmdformats_0.3.7           
##  [39] locfit_1.5-9.4              bitops_1.0-6               
##  [41] DelayedArray_0.14.0         scales_1.1.1               
##  [43] nnet_7.3-14                 gtable_0.3.0               
##  [45] sva_3.36.0                  RProtoBufLib_2.0.0         
##  [47] rlang_0.4.6                 genefilter_1.70.0          
##  [49] scatterplot3d_0.3-41        flowUtils_1.52.0           
##  [51] splines_4.0.0               hexbin_1.28.1              
##  [53] BiocManager_1.30.10         yaml_2.2.1                 
##  [55] abind_1.4-5                 IDPmisc_1.1.20             
##  [57] RBGL_1.64.0                 tools_4.0.0                
##  [59] bookdown_0.19               ellipsis_0.3.1             
##  [61] RColorBrewer_1.1-2          proxy_0.4-24               
##  [63] BiocGenerics_0.34.0         Rcpp_1.0.4.6               
##  [65] plyr_1.8.6                  base64enc_0.1-3            
##  [67] zlibbioc_1.34.0             purrr_0.3.4                
##  [69] RCurl_1.98-1.2              FlowSOM_1.20.0             
##  [71] openssl_1.4.1               S4Vectors_0.26.1           
##  [73] zoo_1.8-8                   SummarizedExperiment_1.18.1
##  [75] haven_2.3.1                 cluster_2.1.0              
##  [77] magrittr_1.5                ncdfFlow_2.34.0            
##  [79] data.table_1.12.8           RSpectra_0.16-0            
##  [81] openxlsx_4.1.5              gmodels_2.18.1             
##  [83] lmtest_0.9-37               RANN_2.6.1                 
##  [85] pcaMethods_1.80.0           matrixStats_0.56.0         
##  [87] hms_0.5.3                   evaluate_0.14              
##  [89] xtable_1.8-4                smoother_1.1               
##  [91] XML_3.99-0.3                rio_0.5.16                 
##  [93] jpeg_0.1-8.1                mclust_5.4.6               
##  [95] readxl_1.3.1                IRanges_2.22.2             
##  [97] gridExtra_2.3               ggcyto_1.16.0              
##  [99] compiler_4.0.0              tibble_3.0.1               
## [101] KernSmooth_2.23-17          crayon_1.3.4               
## [103] htmltools_0.4.0             mgcv_1.8-31                
## [105] corpcor_1.6.9               tidyr_1.1.0                
## [107] RcppParallel_5.0.1          DBI_1.1.0                  
## [109] tweenr_1.0.1                MASS_7.3-51.6              
## [111] boot_1.3-25                 Matrix_1.2-18              
## [113] car_3.0-8                   gdata_2.18.0               
## [115] parallel_4.0.0              GenomicRanges_1.40.0       
## [117] forcats_0.5.0               pkgconfig_2.0.3            
## [119] rvcheck_0.1.8               prettydoc_0.3.1            
## [121] foreign_0.8-80              laeken_0.5.1               
## [123] sp_1.4-2                    xml2_1.3.2                 
## [125] annotate_1.66.0             XVector_0.28.0             
## [127] digest_0.6.25               tsne_0.1-3                 
## [129] ConsensusClusterPlus_1.52.0 graph_1.66.0               
## [131] rmarkdown_2.2               cellranger_1.1.0           
## [133] edgeR_3.30.3                curl_4.3                   
## [135] gtools_3.8.2                ggplot.multistats_1.0.0    
## [137] nlme_3.1-148                lifecycle_0.2.0            
## [139] jsonlite_1.6.1              carData_3.0-4              
## [141] BiocNeighbors_1.6.0         askpass_1.1                
## [143] limma_3.44.3                pillar_1.4.4               
## [145] DEoptimR_1.0-8              survival_3.2-3             
## [147] glue_1.4.1                  xts_0.12-0                 
## [149] zip_2.0.4                   png_0.1-7                  
## [151] bit_1.1-15.2                Rgraphviz_2.32.0           
## [153] ggforce_0.3.1               class_7.3-17               
## [155] stringi_1.4.6               blob_1.2.1                 
## [157] RcppHNSW_0.2.0              CytoML_2.0.5               
## [159] latticeExtra_0.6-29         memoise_1.1.0              
## [161] dplyr_1.0.0                 cytolib_2.0.3              
## [163] knn.covertree_1.0           irlba_2.3.3                
## [165] e1071_1.7-3

Version

0.99.6